This paper discusses methods for evaluating the impacts of social programs prior to their implementation. Ex ante evaluation is useful for designing programs that achieve some optimality criteria, such as maximizing impact for a given cost. This paper illustrates through several examples the use of behavioral models in predicting the impacts of hypothetical programs. Among the programs considered are wage subsidy programs, conditional cash transfer programs, and income support programs. In some cases, the behavioral model justifies a completely nonparametric estimation strategy, even when there is no direct variation in the policy instrument. In other cases, stronger modeling and/or functional form assumptions are required to evaluate a program ex ante. We illustrate the application of ex ante evaluation methods using data from the PROGRESA school subsidy experiment in Mexico. We assess the effectiveness of the method by comparing ex ante predictions of program impacts to the impacts measured under the randomized experiment.
